1 citations · 1 across the 4 of their papers we have counts for
4 papers
Battery and Hydrogen Energy Storage Control in a Smart Energy Network with Flexible Energy Demand using Deep Reinforcement Learning
Cephas Samende, Zhong Fan, Jun Cao
Smart energy networks provide for an effective means to accommodate high penetrations of variable renewable energy sources like solar and wind, which are key for deep decarbonisati…
The role of living laboratories in unlocking the potential of low-carbon energy technologies on the journey to net-zero
Zhong Fan, Jun Cao, Taskin Jamal +8
We demonstrate the potential role of one of the largest at scale multi-vector Smart Energy Network Demonstrator (SEND).
Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning
Daniel J. B. Harrold, Jun Cao, Zhong Fan
In this paper, multi-agent reinforcement learning is used to control a hybrid energy storage system working collaboratively to reduce the energy costs of a microgrid through maximi…
Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints
Cephas Samende, Jun Cao, Zhong Fan
In this paper, we investigate an energy cost minimization problem for prosumers participating in peer-to-peer energy trading. Due to (i) uncertainties caused by renewable energy ge…